Penny Stocks King: How 2 really Trade Penny Stocks (6+Hours)
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5.0 (358)·6h 26m · 47 lectures
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Econometrics for Finance, Economics & Data Science
Master regression, time series, forecasting, financial econometrics, and real-world data analysis with practical example
5.01 reviews119 learners
- All Levels
- 26h 55m video
- 73 lectures
- English
- Updated 2026
Taught by Piyush Dave
- 26h 55m of on-demand video
- 73 lectures across 10 sections
- One-off payment — no subscription
- Lifetime access on web and mobile
- English audio
Curriculum
10 sections73 lectures26h 55m total
- Course Introduction2:44
- Course Introduction In Detail9:07
- What is Econometrics?38:17
- Types of Data32:37
- The Econometric Methodology29:27
- Random Variables & Distributions30:35
- Expected Value & Variance21:01
- Normal Distribution29:40
- Hypothesis Testing Basics25:47
- Confidence Intervals23:19
- The Concept of Regression28:35
- The OLS Method24:43
- Interpreting Coefficients31:23
- Goodness of Fit - R-Squared29:03
- Assumptions of OLS (CLRM)20:40
- Financial Application - Simple Regression30:53
- The t-Test27:45
- The F-Test28:39
- Financial Application - Beta Testing26:44
- p-Values Explained32:30
- Confidence Intervals in Regression30:12
- Interpreting Multiple Coefficients30:31
- Adding More Variables30:02
- Adjusted R-Squared14:34
- Multicollinearity19:41
- Dummy Variables27:37
- Financial Application - Multi-Factor30:45
- Residual Analysis26:11
- Omitted Variable Bias15:34
- Functional Form: Log Models26:10
- Structural Breaks21:18
- Financial Application - Model Diagnostics23:46
- What Is Heteroscedasticity?23:37
- Consequences for OLS20:11
- Detection Tests25:10
- Remedies - Robust Standard Errors30:52
- Financial Application - Volatility Clustering24:13
- What Is Autocorrelation?22:47
- The Durbin-Watson Test22:38
- Remedies for Autocorrelation20:29
- Financial Application - Random Walk Test20:38
- Introduction to Time Series24:25
- Stationarity27:25
- Unit Root Tests - ADF Test23:50
About this course
Econometrics is one of the most valuable analytical skills for students, researchers, economists, finance professionals, and data analysts. This comprehensive course is designed to help you master econometric techniques from the fundamentals to advanced applications through a practical and structured learning approach. You'll begin by understanding the statistical foundations required for econometrics before moving into simple and multiple regression analysis, hypothesis testing, model building, and interpretation…
Before you start
- No prior knowledge of econometrics is required. Basic mathematics and statistics are helpful but not mandatory. Anyone interested in data analysis, economics, finance, or research can follow this course. Familiarity with Excel is beneficial, and examples using R/Python are optional.
Who it’s for
- This course is designed for undergraduate and postgraduate students, MBA and economics learners, finance professionals, data analysts, researchers, aspiring data scientists, CFA/FRM candidates, and anyone who wants to master econometrics for academic, business, or financial applications. It is suitable for both beginners and professionals looking to strengthen their analytical skills.
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